AI-Powered Marketing Optimization

In this project, student teams will explore how AI can enhance marketing campaigns, streamline content creation, and improve customer engagement. Teams will analyze a current marketing process, identify areas where AI can add value, and test AI-powered tools to generate insights, optimize messaging, or personalize campaigns. Primary Organizational Goals for AI Readiness & Adoption: (e.g. improve SEO rankings, automate content creation, personalize marketing campaigns) Current Use of AI (if any): Key Challenges or Opportunities Identified: (e.g. low organic reach, inconsistent brand voice, time-consuming content production)

AI-Driven Organizational Strategy

In this project, student teams will explore how AI integration can redefine organizational efficiency, competitive positioning, and long-term business strategy. Teams will analyze a specific workflow or decision-making process to identify where AI-driven transformation can unlock hidden value and benchmark 2 to 3 AI tools to generate insights, forecast outcomes, and support strategic planning. Primary Organizational Goals for AI Readiness & Adoption: (e.g., optimizing grant distribution, forecasting long-term community needs, identifying untapped market opportunities, identifying growth opportunities) Current Use of AI (if any): Key Challenges or Opportunities Identified: (e.g., scaling impact with limited human resources, lack of data-driven decision-making)

AI Adoption & Internal Training

In this project, student teams will design the frameworks, guidelines, and training resources necessary for responsible AI adoption. The focus is on bridging the gap between technical potential and employee execution. Teams can design a starter set of AI usage guidelines for a specific function or support a pilot group with prompt engineering basics and responsible AI practices that ensures AI tools are used effectively, ethically, and in alignment with organizational standards. Primary Organizational Goals for AI Readiness & Adoption: (e.g., ensuring 100% compliance with data privacy while using Gen-AI, standardizing output quality across marketing and ops) Current Use of AI (if any): Key Challenges or Opportunities Identified: (e.g., lack of standardized "best practices" for prompt engineering)

AI-Driven Data Analytics

In this project, student teams will explore how AI can enhance data analytics. Teams will evaluate AI tools to clean, categorize, or tag a defined dataset (e.g., donor records, sales logs) and recommend an approach to reduce manual effort or consult on a Generative AI approach to summarize a specific data set or build a lightweight dashboard concept for decision support. Primary Organizational Goals for AI Readiness & Adoption: (e.g., improve decision-making with analytics, automate data visualizations, automate data cleaning) Current Use of AI (if any): Key Challenges or Opportunities Identified: (e.g., poor data quality, lack of actionable insights)

AI-Enhanced Operations & Process Automation

In this project, student teams will explore how AI can optimize a specific operational workflow and automate repetitive business processes. Teams will analyze an identified inefficiency or bottleneck, and benchmark AI tools to streamline tasks, improve forecasting, and enhance overall productivity. Deliverables may include workflow automation plans, process mapping with AI integration, forecasting models, and actionable recommendations for implementing AI-driven operational improvements. Primary Goals for AI Readiness & Adoption: (e.g., streamline workflows, automate repetitive tasks, improve supply chain forecasting) Current Use of AI (if any): Key Challenges or Opportunities Identified: (e.g., manual data entry, inefficient scheduling, bottlenecks in approval processes)